code: def forward(self, x, hidden):
      emb = self.drop(self.embedding_layer(x))
      output, hidden = self.rnn(emb, hidden)
      output = self.drop(output)
      output = output.view(-1, output.size(2))
      output = self.output_layer(output)
      return output, hidden
  
imports: import sys
  import os
  import argparse
  import time
  import random
  import math
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import sru
label_desc: Use image node_id 3 for calling the Model obj's underlying member method code with example usage: obj.forward(x, hidden) and returns: output,  hidden